Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation
The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating rand...
| Main Authors: | , |
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| Format: | Article |
| Language: | Arabic |
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College of Science for Women, University of Baghdad
2022-02-01
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| Series: | Baghdad Science Journal |
| Subjects: | |
| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5256 |
| _version_ | 1818331682841821184 |
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| author | Alaa Noori Mazher Jumana Waleed |
| author_facet | Alaa Noori Mazher Jumana Waleed |
| author_sort | Alaa Noori Mazher |
| collection | DOAJ |
| description |
The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order to provide high-quality random, unpredictable, and non-regenerated keys, the chaotic map has been used in the proposed system. In the experiments, the NIST statistical analysis which includes ten statistical tests has been employed to check the randomness of the generated binary bits key. The obtained random cryptographic keys are successful in the tests of NIST, in addition to a considerable degree of aperiodicity.
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| first_indexed | 2024-12-13T13:23:44Z |
| format | Article |
| id | doaj.art-27070cee5e214a9ba26e11d83b7b20c5 |
| institution | Directory Open Access Journal |
| issn | 2078-8665 2411-7986 |
| language | Arabic |
| last_indexed | 2024-12-13T13:23:44Z |
| publishDate | 2022-02-01 |
| publisher | College of Science for Women, University of Baghdad |
| record_format | Article |
| series | Baghdad Science Journal |
| spelling | doaj.art-27070cee5e214a9ba26e11d83b7b20c52022-12-21T23:44:20ZaraCollege of Science for Women, University of BaghdadBaghdad Science Journal2078-86652411-79862022-02-0119110.21123/bsj.2022.19.1.0179Retina Based Glowworm Swarm Optimization for Random Cryptographic Key GenerationAlaa Noori Mazher 0Jumana Waleed1Department of Computer Science, University of Technology, Baghdad, IraqDepartment of Computer Science, College of Science, University of Diyala, Iraq The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order to provide high-quality random, unpredictable, and non-regenerated keys, the chaotic map has been used in the proposed system. In the experiments, the NIST statistical analysis which includes ten statistical tests has been employed to check the randomness of the generated binary bits key. The obtained random cryptographic keys are successful in the tests of NIST, in addition to a considerable degree of aperiodicity. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5256Retina, Glowworm Swarm Optimization (GSO), Chaotic map, Random cryptographic key generation |
| spellingShingle | Alaa Noori Mazher Jumana Waleed Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation Baghdad Science Journal Retina, Glowworm Swarm Optimization (GSO), Chaotic map, Random cryptographic key generation |
| title | Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation |
| title_full | Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation |
| title_fullStr | Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation |
| title_full_unstemmed | Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation |
| title_short | Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation |
| title_sort | retina based glowworm swarm optimization for random cryptographic key generation |
| topic | Retina, Glowworm Swarm Optimization (GSO), Chaotic map, Random cryptographic key generation |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5256 |
| work_keys_str_mv | AT alaanoorimazher retinabasedglowwormswarmoptimizationforrandomcryptographickeygeneration AT jumanawaleed retinabasedglowwormswarmoptimizationforrandomcryptographickeygeneration |